What is Azure Pipelines?

Azure Pipelines is Microsoft's cloud CI/CD service, part of Azure DevOps, used to build, test, and deploy applications to almost any platform or cloud.

Is Azure Pipelines only for Azure deployments?

No, despite the name, Azure Pipelines can build and deploy to non-Azure targets, including on-premises servers, other clouds, and Kubernetes clusters anywhere.

Can Azure Pipelines work with GitHub?

Yes, Azure Pipelines can use a GitHub repository as its source and report build status back to GitHub pull requests, even without using other Azure DevOps services.

What is the difference between YAML and classic pipelines in Azure Pipelines?

YAML pipelines are defined as code in a file committed to the repository, while classic pipelines are configured through a visual, form-based editor in the Azure DevOps UI.

Does Azure Pipelines support Kubernetes deployments?

Yes, Azure Pipelines has built-in tasks for deploying to Kubernetes, including AKS, using manifests or Helm charts.

DevOps

Azure Pipelines

By Microsoft

IntermediateService6K learners

Azure Pipelines is a cloud-based continuous integration and continuous delivery service, part of the Azure DevOps suite, that builds, tests, and deploys code across virtually any language, platform, and cloud.

#AzurePipelines #DevOps#Service#Intermediate#AWSCodePipeline #GoogleCloudBuild #GitHubActions #Kubernetes #SoftwareDelivery#Glossary#SkillVeris

Definition

Azure Pipelines is a cloud-based continuous integration and continuous delivery service, part of the Azure DevOps suite, that builds, tests, and deploys code across virtually any language, platform, and cloud.

Overview

Azure Pipelines lets teams define builds and releases either through YAML pipelines checked into source control or through a classic visual designer, and it supports Microsoft-hosted agents (Windows, Linux, and macOS) as well as self-hosted agents for private infrastructure. As part of Azure DevOps, it sits alongside Azure Repos, Boards, and Artifacts, but it is also commonly used with code hosted outside Azure, including GitHub repositories. Pipelines can build applications targeting .NET, Java, Node.js, Python, and many other stacks, package and push Docker images to a registry, and deploy to targets ranging from Azure App Service and Kubernetes to on-premises servers. It is frequently evaluated against other cloud CI/CD services such as AWS CodePipeline and Google Cloud Build, and against platform-native options like GitHub Actions for teams already using GitHub.

Key Features

YAML-based pipelines checked into source control, or a classic visual editor
Microsoft-hosted build agents for Windows, Linux, and macOS
Support for self-hosted agents on private infrastructure
Multi-stage pipelines covering build, test, and deployment
Deployment to Azure services, Kubernetes, and on-premises targets
Release gates and approvals for controlled production deployments
Integration with Azure Repos, Azure Boards, and GitHub

Use Cases

Building and testing applications across multiple languages and platforms

Deploying to Azure App Service, AKS, or virtual machines

Running gated, multi-stage release pipelines with approvals

Building container images and pushing them to a registry

Standardizing CI/CD for organizations already using Azure DevOps

Frequently Asked Questions

From the Blog

Cloud & Cybersecurity

AWS vs Azure vs Google Cloud: Which to Learn?

A comprehensive guide to aws vs azure vs google cloud: which to learn? — written for learners at every level.

Scikit-Learn for Beginners: Machine Learning in Python

Scikit-learn is the most widely used Python library for classical machine learning. This guide covers the fit-predict workflow, train/test splits, classification, regression, model evaluation, feature engineering, and pipelines — everything you need to build and evaluate your first ML models.